干旱监测与预报研究进展与展望

Research progresses and prospects of drought monitoring and prediction

我国干旱灾害频发,严重威胁国家粮食安全、水安全和生态安全,准确的干旱监测和预报是应对干旱的重要非工程措施。以干旱监测和预报技术为重点,综述了近年来的研究进展与发展方向。首先从单变量和综合干旱指标、数据获取方式两个方面梳理了干旱监测技术的主要进展;其次从干旱发生机理、统计学预报、动力学预报、混合预报、集合预报方面系统总结了干旱预报技术的主要进展;最后对未来干旱监测和预报研究进行了展望。总体上,干旱监测的主要进展集中于基于多源数据的综合干旱指标研究,干旱预报的主要进展集中于基于气候系统模式的动力学预报,同时统计学-动力学混合预报及集合预报发展迅速。未来需要在发展有效干旱指标、改进干旱预报模型、加强变化环境下干旱监测和预报等方面深入研究,提高复杂干旱情势监测预报的精度。

Droughts occur frequently in China,threatening the food security,water security,and ecological security of the nation.Accurate drought monitoring and prediction plays an important role in coping with droughts and reducing their impacts.By taking the techniques of drought monitoring and prediction as the study focuses,the relevant research progresses and development trends in recent years are reviewed herein.Firstly,the main progresses of the drought monitoring techniques are sorted out from the aspects of the univariate/comprehensive drought indices and the data acquisition mode,and then the main progresses of the drought prediction techniques are systematically summarized from the aspects of the drought occurrence mechanism,statistical prediction,dynamic prediction,hybrid prediction and ensemble prediction,and finally,the studies to be made on the drought monitoring and prediction in the days to come are prospected.Generally,the main progresses of the drought monitoring are concentrated on the multi-source data-based study of the comprehensive drought index,while the main progresses of the drought prediction are mainly concentrated on the climate system model-based dynamic prediction,along with the statistic-dynamic hybrid prediction and the ensemble prediction that are under rapid development.Future studies on the aspects of developing effective drought indices,improving drought prediction model,enhancing the drought monitoring and prediction under changing environment,etc.are necessary to be made in the days to come,so as to improve the accuracies of monitoring and prediction of complicated drought conditions.